Determination of a growth—environment relationship in jute (Corchorus olitorius L.)

Agricultural Meteorology, 22 (1980) 45--52 Elsevier Scientific Publishing Company, Amsterdam -- Printed in The Netherlands

45

DETERMINATION OF A GROWTH--ENVIRONMENT RELATIONSHIP IN JUTE (Corchorus olitorius L.)

P. V. RAO

Jute Agricultural Research Institute (I.C.A.R.), Barrackpore 743101, West Bengal (India) (Received September 11, 1978; accepted January 16, 1979)

ABSTRACT Rao, P. V., 1980. Determination of a growth--environment relationship in jute (Corchorus olitorius L). Agric. Meteorol., 22: 45--52. Average daily growth rates of four varieties of jute (C. olitorius) were found from weekly observations of crop height in the field, and were analysed in relation to relevant environmental data from a nearby crop-weather station. Two-factor correlation analyses were made between the daily growth rates and average weather variables, age and cumulative growth of the crop. Multiple-regression analyses were derived taking the growth rate as dependent variable, and the significant weather parameters, namely weekly means of maximum and m i n i m u m air temperatures, morning soil temperature (5 cm depth) and mean daily rainfall, together with the plant factors, age and cumulative growth, as independent variables. The regression equations were tested on independent weather and crop data. The close agreement of the calculated ("predicted") values with the actual recorded growth rates and cumulative growth indicates that the system offers promise for the prediction of growth by the use of environmental factors.

INTRODUCTION

Extensive experiments and research have provided the basic information regarding the culture and methods of treatment needed for the successful production of crops under field conditions. Such information includes the selection of appropriate geographical locations, optimum fertilization, irrigation requirement and effective methods of plant protection. Even so, crop yields fluctuate considerably from year to year, a fact attributable to the variation in environmental conditions. Although the weather cannot in practice be controlled under field conditions, it is of considerable value to know the precise influence of various environmental factors on crop growth. Furthermore, such knowledge facilitates the delimitation of potential crop production areas. The present study was designed to evaluate the influence of environmental factors on the growth of jute (Corchorus olitorius) and to produce growth prediction formulae. © 1980 Elsevier Scientific Publishing Company

46 MATERIALS AND METHODS

There are two cultivated species of jute, namely Corchorus olitorius and C. capsularis, of the family Tiliaceae. Jute fibre is obtained from the bark of the plants, so that good vegetative growth is essential for better yields. Research has shown that there is a high positive correlation between plant height and fibre yield. Consequently, the height of the jute plant was taken as an indicator of plant growth and yield. Moreover, height observations were non-destructive, so that continuous development of individual plants could be followed throughout the growing season. The field experiment was carried out for four years, 1973--1976. The crop was sown in split-plot design with four replications, three dates of sow, ing and four varieties, namely J R O 632, JRO 3690, J R O 7835 and J R O 878. As the experiment was conducted entirely under rain-fed conditions, the sowings were done between March and May whenever soil moisture conditions were favourable. The crop was subjected to normal r e c o m m e n d e d fertilize! treatment and to plant protection measures. Five plants were selected in each plot, randomly from the inner rows, and as a result 20 plants were taken as representative of each variety, and were tagged so that repeat observations could be made throughout the season. Plant height measurements were made at weekly intervals, and dally growth rates were ascertained by subtracting the 20-plant mean height at the previous observation from the current mean height, then dividing by the number of days between observations. Air temperature, 5 cm soil temperature, rainfall, water evaporation and relative humidity were recorded daffy at 06h36 and 13h36 at a cropweather station situated near the experimental field. Sunshine duration data were recorded by the India Meteorological Department at Dum Dum, Calcutta, some 5 km from the experimental site. These parameters were averaged over weekly periods corresponding to the various growth periods. Growth rates in the years 1973, 1974 and 1976 were taken together and two-factor correlation analyses were made between the daily growth rates and the meteorological variables, the age of the crop and the cumulative growth. Variables which showed a significant correlation were then used in the construction of a multiple-regression equation for each separate variety. These 'prediction' equations were then tested by application to independent data of 1975, which had n o t been used in their construction. RESULTS AND DISCUSSION

The characteristic growth curve of jute is shown in Fig.1. The growth was slow and exponential during the early period, b u t became more or less linear after 30 days and remained so until flowering, after which it decreased substantially. The week-to-week fluctuations in growth rate from point A to point B were taken as reflections of 'better' or 'poorer' growth conditions, which could be attributable to environmental conditions.

47

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Fig.1. G r o w t h curve of J R O 878.

Growth rates for three dates of sowing in 1976 are shown in Fig.2., the fluctuations being similar among sowings. The magnitudes of the fluctuations were, however, different between sowings although the plants were exposed to the same environmental conditions. These differences may be attributed to age and, consequently, to state of plant growth, which implied that age and cumulative growth should be included as independent variables in developing a growth-prediction system. Table I shows the correlations between the growth rates of the four jute varieties and the environmental factors, the age and the cumulative growth of the crop. Maximum air temperature, minimum air temperature and morning (5 cm) soil temperature were positively and highly correlated with growth rate. Rainfall showed significant negative correlation, indicating that high rainfall which results in water-logging is detrimental to healthy crop growth. The regression equations for the relationships of growth rate to temperature revealed that growth would cease when the day-time air temperatures fell below 21°C, and when the night-time air and soil temperatures fell below 20°C. There was little difference in these threshold temperatures between the varieties. The age and cumulative growth of the crop were, as might be expected, negatively and highly correlated.

6.0 GERMINATION

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Variables

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Max. temperature (°C) Min. temperature (°C) Rainfall (mm) 5 cm soil temp.: morning (°C) afternoon (°C) Sunshine duration (h) Pan evaporation (ram) Relative humidity (%) Cumulative growth (cm) Age of the crop (days)

0.3181"* 0.2710"* --0.2150" 0.2411" 0.0719 --0.0962 --0.1482 -0.0869 -0.4156"** --0.6065***

0.3034** 0.3104"* -0.2120" 0.2454* 0.0783 -0.0939 0.1214 -0.0707 -0.3996*** -0.5803***

0.2808** 0.2915"* -0.2480* 0.2511" 0.0774 -0.1082 0.1013 -0.0660 -0.4226*** -0.5736***

0.3150"* 0.3059** -0.2652** 0.2653** 0.0670 -0:1366 0.1160 --0.0574 -0.4409*** -0.5842***

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Multiple-regression formulae were derived for growth rates using six significant p~rameters as indePendent variables and 26, 29 and 43 sets of data from 1973, 1974 and 19~6, respectively. Table II shows the results of these analyses for the four varieties. The resulting equations seem to provide a good evaluation of thegrowth rate--environment relationship. The coefficient of determination (R 2 )

49 TABLE II Results of multiple regression analyses for different jute varieties, with growth rate as the dependent variable Independent variable

Partial regression coefficients: JRO 632 JRO 3690 JRO 7835

JRO 878

Maximum temp. (°C) Minimum temp. (°C) Av. daily rainfall (mm) Morning 5 cm soil temp. (°C) Age of crop (days) Cumulative growth (cm) Regression constant Degrees of freedom Coefficient multiple correlation Coefficient determination F-value

-0.197 0.129 -0.050*** 0.314 -0.0750*** 0.0177 -0.148 98 0.9737 0.9480 277

-0.049 0.260 -0.039* -0.01 -0.0682*** 0.0137 0.805 98 0.9689 0.9388 233

-0.152 0.186 -0.052** 0.196 -0.0704*** 0.0147 0.425 98 0.9741 0.9488 281

-0.039 0.187 -0.034* 0.154 -0.0726*** 0.0182 -2.725 98 0.9730 0.9468 270

*, **, and *** indicate significance at 0.05, 0.01 and 0.001 levels of probability, respectively.

i n d i c a t e d t h a t a b o u t 94% o f t h e v a r i a t i o n c o u l d be a c c o u n t e d for. F u r t h e r m o r e , F-values were v e r y highly significant at t h e 0.001 level. H o w e v e r , high F a n d R 2 values d o n o t necessarily i m p l y a c c u r a c y t o an e q u a t i o n which is used for the purpose of prediction. T h e o n l y c o n v i n c i n g t e s t o f such a c c u r a c y is t h e a p p l i c a t i o n o f t h e e q u a t i o n s t o a n o t h e r e n t i r e l y u n r e l a t e d set o f d a t a f r o m a n o t h e r y e a r which has n o t b e e n u s e d in t h e i r c o n s t r u c t i o n . G r o w t h rates, t h e r e f o r e , w e r e calc u l a t e d f o r all f o u r varieties using t h e w e a t h e r a n d c r o p d a t a f o r 1 9 7 5 , a n d the results are p r e s e n t e d in Fig.3. T h e o b s e r v e d a n d p r e d i c t e d g r o w t h rates a n d r e s u l t a n t c u m u l a t i v e g r o w t h are in relatively g o o d a g r e e m e n t . Close s c r u t i n y revealed t h a t the regressions over- or u n d e r - e s t i m a t e d values d u r i n g t h e f h s t 60 d a y s of c r o p g r o w t h . F r o m a b o u t 40 d a y s o f c r o p age until harvest, t h e f l u c t u a t i o n s in o b s e r v e d a n d p r e d i c t e d g r o w t h r a t e s are q u i t e similar. T h e final e s t i m a t e d c u m u l a t i v e g r o w t h agrees well w i t h t h e actual value f o r all varieties. This s t u d y illustrates t h e p o s s i b i l i t y o f e v a l u a t i n g p l a n t r e s p o n s e s t o e n v i r o n m e n t a l f a c t o r s a n d so p r e d i c t i n g t h e g r o w t h w h i c h gives an e s t i m a t e o f fibre yield. T h e analyses p r e s e n t e d h e r e s h o u l d n o t be c o n s i d e r e d as exclusive or u n i q u e in t h e i r a t t e m p t t o q u a n t i f y the i n f l u e n c e o f environm e n t a l factors. T h e f a c t t h a t these e q u a t i o n s s h o w i n a d e q u a c i e s in t h e first 60 d a y s of c r o p age indicates t h a t f u r t h e r i m p r o v e m e n t is n e c e s s a r y , a n d w o r k is p r o c e e d i n g o n this p r o b l e m .

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52 Such prediction equations can be applied in the evaluation of potential areas of production. Moreover, the acceleration or retardation in growth rate due to application of growth regulators, chemical pesticides etc. may also be detected with the help of such formulae. ACKNOWLEDGEMENTS I am grateful to Dr. T. Ghosh, Director of the Jute Agricultural Research Institute, Barrackpore, for the advice and encouragement in conducting the work, and also for critically going through the manuscript. Furthermore, I am thankful to Professor R. Ramanadham, Head of the Department of Meteorology and Oceanography, Andhra University, Waltair, for advice on the analyses.